Rapid improvements in emotion regulation predict eating disorder psychopathology and functional impairment at 6‐month follow‐up in individuals with bulimia nervosa and purging disorder
Bibliographic record
Abstract
OBJECTIVE: We previously demonstrated that early improvements in access to emotion regulation strategies during the first 4 weeks of intensive cognitive behavior therapy (CBT)-based eating disorder (ED) treatment predicted a range of post-treatment outcomes. This follow-up article examines whether early improvements in access to emotion regulation strategies continue to predict good treatment outcomes at 6 months post-treatment. METHOD: Participants were 76 patients with bulimia nervosa or purging disorder who participated in the original study and the 6-month follow-up assessment. Hierarchical regression models were used to examine whether early improvements in emotion regulation strategies predicted 6-month follow-up outcomes. RESULTS: After controlling relevant covariates and rapid and substantial behavior change, greater early improvements in access to emotion regulation strategies during the first 4 weeks of intensive treatment predicted lower overall ED psychopathology and ED-related functional impairment 6 months after treatment. They did not predict abstinence from binge, vomit, and laxative use behaviors during the follow-up period. DISCUSSION: Individuals who learn early in treatment that they can use skills to more effectively regulate emotions have better treatment outcomes on some variables 6 months after treatment. Teaching emotion regulation skills in the first phase of CBT for ED may be beneficial, particularly for individuals with baseline difficulties.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".